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A computationally engineered RAS rheostat reveals RAS–ERK signaling dynamics

Nature Chemical Biology volume 13, pages 119–126 (2017)Cite this article

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Abstract

Synthetic protein switches controlled with user-defined inputs are powerful tools for studying and controlling dynamic cellular processes. To date, these approaches have relied primarily on intermolecular regulation. Here we report a computationally guided framework for engineering intramolecular regulation of protein function. We utilize this framework to develop chemically inducible activator of RAS (CIAR), a single-component RAS rheostat that directly activates endogenous RAS in response to a small molecule. Using CIAR, we show that direct RAS activation elicits markedly different RAS–ERK signaling dynamics from growth factor stimulation, and that these dynamics differ among cell types. We also found that the clinically approved RAF inhibitor vemurafenib potently primes cells to respond to direct wild-type RAS activation. These results demonstrate the utility of CIAR for quantitatively interrogating RAS signaling. Finally, we demonstrate the general utility of our approach in design of intramolecularly regulated protein tools by applying it to the Rho family of guanine nucleotide exchange factors.

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Figure 1: Strategy for engineering CIAR.
Figure 2: Computational framework for designing CIAR.
Figure 3: CIAR functions as a RAS rheostat.
Figure 4: Interrogation of RAF regulation with CIAR.
Figure 5: Phosphoproteomic comparison of direct RAS activation and EGF stimulation in CIAR-293 cells.
Figure 6: Computational design of inducible Rho family GEFs.

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Acknowledgements

E. Campeau (Zenith Epigenetics) provided the pLenti_CMV_GFP_Puro (658-5) plasmid, and M. Meyerson (Dana-Farber Cancer Institute) provided pBABEpuro-CRAF. This research was supported by US National Institutes of Health (NIH) grants R01GM086858 (D.J.M.), R01CA126792 (J.D.) and F30CA189793 (J.C.R.), a National Science Foundation CAREER award CHE-0954242 (D.J.M.), the US Department of Defense Breast Cancer Research Program (BCRP) (W81XWH-11-1-0130) and the Howard Hughes Medical Institute (P.-S.H. and D.B.).

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  1. Po-Ssu Huang

    Present address: Present address: Department of Bioengineering, Stanford University, Stanford, California, USA.,

Authors and Affiliations

  1. Department of Chemistry, University of Washington, Seattle, Washington, USA

    John C Rose, Bridget M Trevillian, Miles S Dickinson, Daniel Cunningham-Bryant & Dustin J Maly

  2. Department of Biochemistry, University of Washington, Seattle, Washington, USA

    Po-Ssu Huang, Inna Goreshnik, David Baker & Dustin J Maly

  3. Institute for Protein Design, University of Washington, Seattle, Washington, USA

    Po-Ssu Huang & David Baker

  4. Department of Genome Sciences, University of Washington, Seattle, Washington, USA

    Nathan D Camp & Alejandro Wolf-Yadlin

  5. Department of Pathology and Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, USA

    Jordan Ye, Andrew M Leidal & Jayanta Debnath

  6. Howard Hughes Medical Institute, University of Washington, Seattle, Washington, USA

    David Baker

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Contributions

J.C.R. and D.J.M. conceived the project and designed the study. J.C.R. and P.-S.H. developed computational methods and performed the design calculations with guidance from D.B. J.C.R., I.G., and D.C.-B. performed biochemical experiments. J.C.R., J.Y., and M.S.D. performed cell biology experiments under the supervision of J.D. and D.J.M. J.C.R., A.M.L., M.S.D., and B.M.T. generated reagents and cell lines. J.C.R. generated samples for mass spectrometry experiments. N.D.C. prepared peptide samples, performed MS analyses, and processed MS data under the supervision of A.W.-Y. J.C.R., D.J.M., N.D.C., and A.W.-Y. analyzed the MS data. J.C.R., P.-S.H., and D.J.M. wrote the manuscript. All authors read and approved the manuscript.

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Correspondence to Dustin J Maly.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Results and Supplementary Figures 1–32. (PDF 33198 kb)

Supplementary Data Set 1

30 min stimulation phosphoproteomic data set. (XLSX 344 kb)

Supplementary Data Set 2

Time-course phosphoproteomic data set. (XLSX 190 kb)

Supplementary Data Set 3

Class I and class II phosphopeptides. (XLSX 60 kb)

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Rose, J., Huang, PS., Camp, N. et al. A computationally engineered RAS rheostat reveals RAS–ERK signaling dynamics. Nat Chem Biol 13, 119–126 (2017). https://doi.org/10.1038/nchembio.2244

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